Attention is a pivotal resource in the modern economy and plays an increasingly prominent role in economic analysis. We summarize research on attention from both psychology and economics, placing a particular emphasis on its capacity to explain numerous documented violations of classical...

Based on administrative data of unemployed in Belgium, we estimate the labour market effects of three training programmes at various aggregation levels using Modified Causal Forests, a causal machine learning estimator. While all programmes have positive effects after the lock-in period, we find...

To successfully reduce student attrition, it is imperative to understand what the underlying determinants of attrition are and which students are at risk of dropping out. We develop an early detection system (EDS) using administrative student data from a state and a private university to predict...

Artificial intelligence (AI) is starting to pervade the economic and social life rendering strategic interactions with artificial agents more and more common. At the same time, experimental economic research has increasingly employed computer players to advance our understanding of strategic...

While traditional empirical models using determinants like size and trade costs are able to predict RTA formation reasonably well, we demonstrate that allowing for machine detected non-linear patterns helps to improve the predictive power of RTA formation substantially. We employ machine...

Can machine learning support better governance? In the context of Brazilian municipalities, 2001-2012, we have access to detailed accounts of local budgets and audit data on the associated fiscal corruption. Using the budget variables as predictors, we train a tree-based gradient-boosted...

We propose a new method to design a short survey measure of a complex concept such as women’s agency. The approach combines mixed-methods data collection and machine learning. We select the best survey questions based on how strongly correlated they are with a “gold standard” measure of...

We provide a comprehensive overview of the literature on the measurement of democracy and present an extensive update of the Machine Learning indicator of Gründler and Krieger (2016, European Journal of Political Economy). Four improvements are particularly notable: First, we produce a...

Populist parties recently have shaken Western democracies, yet there is no consensus regarding the characteristics of populist voters. By using large-scale surveys from four European countries (France, Germany, Spain, and the U.K.), we investigate individual determinants of populist voting. Our...

This paper sheds new light on the role of communication for cartel formation. Using machine learning to evaluate free-form chat communication among firms in a laboratory experiment, we identify typical communication patterns for both explicit cartel formation and indirect attempts to collude...